How do I install the Mlops skill?

Run npx skillmds@latest add kina2711/mlops in your terminal (requires Node.js), paste this page's agent-chat prompt into Claude, Cursor, or any MCP-connected agent, or download the SKILL.md file and copy it into your agent's skills directory.

Is Mlops safe to use?

This skill has not completed SkillMD's automated safety review yet. SkillMD never runs a skill's scripts for you; review the SKILL.md before installing.

Which AI agents work with Mlops?

This skill is tagged as working with Claude Code, Claude.ai, OpenAI Codex. SKILL.md is an open format, so most agents that read a skills directory can load it too.

Is Mlops free to use?

Yes. Installing skills from SkillMD is free, and the skill stays under its author's original license.

kina2711 (@kina2711) published this skill. Their other Agent Skills are listed on their SkillMD profile.

Mlops by kina2711 — Agent Skill

Name: Mlops
Author: kina2711

Mlops

Operate the ML lifecycle through experiment tracking, registry, CI/CD, deployment, monitoring, drift, retraining, rollback, lineage and governance. Use for MLOps, model release or ML platform operations. The underlying platform belongs to data-platform-and-dataops.

kina2711 b4e5ff0 50 files · 143.2 KB Updated Sep 17, 2026

File contents

MLOps

Operating contract

Identify the requested deliverable, then select exactly one atomic task below.
Read that task file completely before acting.
Read references/lifecycle-standard.md and use the task's profile, risk tier and execution path.
Load only the company context and adapter references needed for the selected task.
On a cross-role handoff, compare logical ID and SHA-256 in references/shared-reference-manifest.json; reuse an already loaded shared reference when both match instead of loading its duplicate.
Inspect real artifacts and systems before making change-sensitive claims.
Apply Definition of Ready, stage gates, test strategy, Definition of Done, approval and handoff requirements.
Do not invent access, approvals, successful execution, test results or business confirmation.
For any Git-backed mutation, regardless of the task's verb or profile, require a pre-change success/scope contract, a post-change core-audit-change-scope, and fresh core-verify-deliverable evidence before completion.
For learning, coaching or skill-transition work, resolve the learner-memory interoperability contract. Reuse only relevant verified summaries; never infer mastery from exposure, and expand stale, uncertain, changed-version or safety-critical prerequisites.

Ownership

Own only deliverables listed in this role catalog. When the requested deliverable belongs to another role, produce a handoff instead of silently taking ownership. Use the department orchestrator for multi-role work.

Stack-native adapter routing

After selecting the task, detect the real stack/version and read only the matching adapter below plus the adapter index. Do not load every adapter.

spark
databricks
mlflow-kubeflow

Atomic task routing

Plan, define, design, map, specify or create a proposed artifact (1 task): read references/catalog-plan-design.md.
Build, implement, configure, teach, interview or deliver an artifact — workflow deliverables (2 tasks): read references/catalog-build-deliver-workflow.md.
Build, implement, configure, teach, interview or deliver an artifact — remaining deliverables (10 tasks): read references/catalog-build-deliver-other.md.
Inspect, analyze, test, review, validate, assess, certify or audit (2 tasks): read references/catalog-test-assure.md.
Deploy, release, monitor, recover, migrate, optimize, retire or improve (8 tasks): read references/catalog-operate-improve.md.

Read only the best-matching catalog. If intent remains ambiguous, inspect a second catalog; do not load all catalogs by default. Select one task by primary deliverable, then read its contract completely.

Completion response

State the selected task ID, primary deliverable, evidence inspected, validation performed, approval status, residual risks and next owner. A draft or plan is not an executed production outcome.

---name: mlopsdescription: Operate the ML lifecycle through experiment tracking, registry, CI/CD, deployment, monitoring, drift, retraining, rollback, lineage and governance. Use for MLOps, model release or ML platform operations. The underlying platform belongs to data-platform-and-dataops.---# MLOps## Operating contract1. Identify the requested deliverable, then select exactly one atomic task below.2. Read that task file completely before acting.3. Read [references/lifecycle-standard.md](references/lifecycle-standard.md) and use the task's profile, risk tier and execution path.4. Load only the company context and adapter references needed for the selected task.5. On a cross-role handoff, compare logical ID and SHA-256 in `references/shared-reference-manifest.json`; reuse an already loaded shared reference when both match instead of loading its duplicate.6. Inspect real artifacts and systems before making change-sensitive claims.7. Apply Definition of Ready, stage gates, test strategy, Definition of Done, approval and handoff requirements.8. Do not invent access, approvals, successful execution, test results or business confirmation.9. For any Git-backed mutation, regardless of the task's verb or profile, require a pre-change success/scope contract, a post-change `core-audit-change-scope`, and fresh `core-verify-deliverable` evidence before completion.10. For learning, coaching or skill-transition work, resolve [the learner-memory interoperability contract](references/learning-memory-interoperability.md). Reuse only relevant verified summaries; never infer mastery from exposure, and expand stale, uncertain, changed-version or safety-critical prerequisites.## OwnershipOwn only deliverables listed in this role catalog. When the requested deliverable belongs to another role, produce a handoff instead of silently taking ownership. Use the department orchestrator for multi-role work.## Stack-native adapter routingAfter selecting the task, detect the real stack/version and read only the matching adapter below plus [the adapter index](references/technology-adapters.md). Do not load every adapter.- [spark](references/adapter-spark.md)- [databricks](references/adapter-databricks.md)- [mlflow-kubeflow](references/adapter-mlflow-kubeflow.md)## Atomic task routing- **Plan, define, design, map, specify or create a proposed artifact** (1 task): read [references/catalog-plan-design.md](references/catalog-plan-design.md).- **Build, implement, configure, teach, interview or deliver an artifact — workflow deliverables** (2 tasks): read [references/catalog-build-deliver-workflow.md](references/catalog-build-deliver-workflow.md).- **Build, implement, configure, teach, interview or deliver an artifact — remaining deliverables** (10 tasks): read [references/catalog-build-deliver-other.md](references/catalog-build-deliver-other.md).- **Inspect, analyze, test, review, validate, assess, certify or audit** (2 tasks): read [references/catalog-test-assure.md](references/catalog-test-assure.md).- **Deploy, release, monitor, recover, migrate, optimize, retire or improve** (8 tasks): read [references/catalog-operate-improve.md](references/catalog-operate-improve.md).Read only the best-matching catalog. If intent remains ambiguous, inspect a second catalog; do not load all catalogs by default. Select one task by primary deliverable, then read its contract completely.## Completion responseState the selected task ID, primary deliverable, evidence inspected, validation performed, approval status, residual risks and next owner. A draft or plan is not an executed production outcome.

Frequently asked questions